Biology subjects

McIntyre, C. C.

Publications and source records attributed to McIntyre, C. C..

8 recordsLinked to original sources

bioRxiv2026

The individuality of single-frame functional brain connectivity

AbstractConverging evidence from studies on brain network "fingerprinting" and precision functional mapping suggest that brain networks are highly individualized in functionally meaningful ways. Concurrently with a growth in studies on this topic, there has been a rise in interest on dynamics (approximately second-to-second changes) in brain networks within scan sessions. While analyses of traditional static networks have increasingly grown towards emphasizing the importance of individual differences in brain network topology, studies of dynamic networks typically follow methodology that require brain states to be considered at a group level. Recent studies have begun to assess the individuality of recurring dynamic brain "states". In this work, we extend this recent work by exploring the extent to which functional connectivity fingerprinting is feasible at single-frame temporal resolution. We estimate connectivity at individual volumes using phase coherence. We find that the identity of participants can be classified based on single volumes given sufficient database scan data and that having more highly parcellated atlases facilitates identification. Finally, we find that tasks can be identified more readily within subjects than between subjects. We conclude that participant identity may be an important driver of observed single-volume connectivity patterns. Further, the single-volume neural correlates of a task appear to be more consistent within subjects than between subjects. This highlights the importance of considering individual variability in studies of brain network dynamics.

neuroscience↗

bioRxiv2025

Poorer physical function is associated with elevated spatial entropy in the aging brain network landscape

Life is a constant struggle against disorder. As we age, our ability to maintain internal order declines. In the healthy human brain, order is observable in the form of functionally segregated brain network communities that exhibit spatial consistency. These communities associate with distinct cognitive and physical functions. When mapped into the brain, they form a functional "landscape". We assessed the spatial disorder of these landscapes in older adults with a wide range of mobility using a modified version of Shannon entropy. We found that compared to younger adults, older adults had significantly higher entropy in the sensorimotor cortex, basal ganglia, hippocampus, thalamus, and occipital lobe. Higher entropy in many of these regions was associated with worse physical function and higher body mass index in older adults. Findings suggest that spatial entropy in brain network landscapes may be a marker of declining physical function. Modifiable factors, such as losing excess weight, may help to ameliorate aging-related brain entropy increases in regions such as the sensorimotor cortex, which may in turn help to preserve physical function in older adults.

neuroscience↗

bioRxiv2025

Spatial entropy of brain network landscapes: a novel method to assess spatial disorder in brain networks

In this work, we introduce a method for mapping the spatial entropy of functional brain network community structure images in brain space. Entropy maps indicate the extent to which the network communities present in a local area are ordered or disordered. We demonstrate how spatial entropy can be quantified for each voxel in the brain according to the network community affiliations of surrounding voxels. This process results in interpretable maps of brain network entropy. We show that local entropy decreases in predictable brain regions during working memory and music-listening tasks. We suggest that these regional entropy reductions reflect self-organization of neural processes in support of functionally localized cognitive tasks. Analyses in this work provide a framework for future analyses of spatial entropy in complex networks that can be mapped to Euclidean space - both within the brain and in other contexts. Significance StatementWe introduce an approach for quantifying the spatial entropy of functional brain network community structure. We demonstrate the biological relevance of the measure in three independent datasets. This approach for analyzing brain network data is data-driven, easy to implement, and highly interpretable. It also allows investigators to visualize complex data by mapping values into the brain rather than storing values in extremely high-dimensional and abstract data structures. We believe this will make the method highly accessible even to investigators with minimal experience analyzing human neuroimaging data.

neuroscience↗

bioRxiv2024

Insulin resistance, cognition, and functional brain network topology in older adults with obesity

ObjectiveCross-sectional data from a sample of older adults with obesity was used to determine how peripheral and neuronal insulin resistance (IR) relate to executive function and functional brain network topology. MethodsOlder adults (n=71) with obesity but without type 2 diabetes were included. Peripheral IR was quantified by HOMA2-IR. Neuronal IR was quantified according to a proposed neuron-derived exosome-based method (NDE-IR). An executive function composite score, summed scores to the Auditory Verbal Learning Test (AVLT) trials 1-5, and functional brain networks generated from resting-state functional magnetic resonance imaging were outcomes in analyses. We used general linear models and a novel regression framework for brain network analysis to identify relationships between IR measures and brain-related outcomes. ResultsHOMA2-IR, but not NDE-IR, was negatively associated with executive function. Neither IR measure was associated with AVLT score. Peripheral IR was also related to hippocampal network topology in participants who had undergone functional neuroimaging. Neither peripheral nor neuronal IR were significantly related to network topology of the central executive network. ConclusionsCognitive and functional imaging effects were observed from HOMA2-IR, but not NDE-IR. The hippocampus may be particularly vulnerable to effects of peripheral IR.

neuroscience↗

bioRxiv2024

Triple network dynamics and future alcohol consumption in adolescents

BackgroundHuman neuroimaging increasingly suggests that the brain is best modeled as a highly interconnected and dynamic system. However, novel methodology for studying functional brain network dynamics have never been applied to the study of adolescent alcohol consumption. We sought to determine whether brain network dynamics are related to future drinking behavior in teenagers. MethodsResting-state functional magnetic resonance imaging (fMRI) time series from 17-year-old non/low drinking participants (n=295) of the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study were used to fit a Hidden Semi-Markov Model (HSMM). Regions of the default mode network (DMN), salience network (SN), and central executive network (CEN), collectively known as the Triple Network, were included in modeling. The HSMM identified the most-likely state sequence for each participant, a trajectory through distinct brain network states over the course of their fMRI scan. Poisson regression models were used to assess relationships between state sequence metrics and future drinking frequency. Potential sex differences in state sequence metrics or the relationship between sequence metrics and future drinking were assessed with permutation testing and interactions in regression models. ResultsNo sex differences in state sequence metrics were observed. However, the relationship between occupancy times and future drinking frequency differed by sex for two brain states. In the full sample, occupancy time in a state characterized by high interconnectivity between the SN and CEN was negatively associated with drinking. Occupancy time in a separate state characterized by high activation in the DMN and SN, but low activation in the CEN, was negatively associated with future drinking. ConclusionsBrain network dynamics may be useful neural markers of predisposition to drinking in adolescents. Brain states which make teens vulnerable or resilient to drinking may differ between sexes.

neuroscience↗

bioRxiv2024

Contrasting topologies of synchronous and asynchronous functional brain networks

We generated asynchronous functional networks (aFNs) using a novel method called optimal causation entropy (oCSE) and compared aFN topology to the correlation-based synchronous functional networks (sFNs) which are commonly used in network neuroscience studies. Functional magnetic resonance imaging (fMRI) time series from 212 participants of the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study were used to generate aFNs and sFNs. As a demonstration of how aFNs and sFNs can be used in tandem, we used multivariate mixed effects models to determine whether age interacted with node efficiency to influence connection probabilities in the two networks. After adjusting for differences in network density, aFNs had higher global efficiency but lower local efficiency than the sFNs. In the aFNs, nodes with the highest outgoing global efficiency tended to be in the brainstem and orbitofrontal cortex. aFN nodes with the highest incoming global efficiency tended to be members of the Default Mode Network (DMN) in sFNs. Age interacted with node global efficiency in aFNs and node local efficiency in sFNs to influence connection probability. We conclude that the sFN and aFN both offer information about functional brain connectivity which the other type of network does not.

neuroscience↗

bioRxiv2022

Decoding Depression During Subcallosal Cingulate Deep Brain Stimulation

AO_SCPLOWBSTRACTC_SCPLOWDeep brain stimulation of subcallosal cingulate white matter (SCCwm-DBS) alleviates symptoms of treatment resistant depression (TRD) over months of therapy. Readouts of depression symptom severity derived from neural recordings are needed for more systematic study and improvement of the therapy. In this study, we measured local field potentials (LFP) multiple times a day alongside seven months of therapy using the Activa PC+S in six patients treated with SCCwm-DBS. We found significant changes in oscillatory power between early and late therapy after accounting for stimulation-related distortions, particularly within the {beta} band. We then used a decoder strategy to identify oscillatory activity that tracked with depression measurements over seven months, with asymmetric{delta} and {beta} oscillations contributing to a statistically significant prediction of 10% of the measured depression signal. Simulating its use in clinical decision-making, we demonstrated that the DR-SCC yield clinically meaningful information that can augment other measures of depression state. Ultimately, this DR-SCC provides a data-driven first-step towards objectively tracking chronic recovery after antidepressant DBS implantation and developing adaptive DBS strategies in the presence of active stimulation.

neuroscience↗

bioRxiv2021

Mimicking and mitigating the cutaneous response to transcranial electrical stimulation using interferential and combinatorial techniques

Transcranial electrical stimulation (tES) is a promising adjunct treatment for neurological impairment and mental health disorders. The modulatory effects of tES are small to moderate, and accrue over days to weeks with repeated administration, but these effects are also inconsistent across individuals, which poses a challenge for its clinical administration. Some of the variability in tES may stem from uncontrolled behavioral factors, and inadequate dosing of current across individuals, so new strategies are needed to address these issues. We evaluated the biophysics of emerging techniques for tES and provided new testable hypotheses for the tolerability of interferentail and combinatorial waveforms. Millisecond pulsatile currents may serve as suitable alternatives to alternating currents in modulating neural spike timing from tES. Pulsatile currents limit spike generation in nerves and may be tolerated above the standard limit of 2 mA when combined with a direct current to block nerve activation. Additionally, we posit that combinations of kilohertz interferential currents can mimic the nerve response of different tES waveforms but with minimal modulation of cortical neurons, providing a new strategy for active placebo stimulation. These results will help guide design of interferential tES strategies for better blinding and provide a testable model for evaluating the tolerability of new combinatorial strategies.

biophysics↗